Melanin

Here is an interesting story:

Researchers at the Albert Einstein College of Medicine (AEC) have found evidence that certain fungi possess another talent beyond their ability to decompose matter: the capacity to use radioactivity as an energy source for making food and spurring their growth.

the researchers measured the electron spin resonance signal after melanin was exposed to ionizing radiation and found that radiation interacts with melanin to alter its electron structure. This, they believe, is an essential step for capturing radiation and converting it into a different form of energy to make food. Until now, melanin’s biological role in fungi – if any – had been a mystery. Interestingly, the melanin in fungi is no different chemically from the melanin in our skin, leading Casadevall to speculate that melanin could be providing energy to skin cells.

In the skin, melanin functions primarily to protect the genetic material from UV light. Melanin can also protect against free radicals and can function as an alternative electron acceptor. This newly discovered function simply adds to the overall utility of this molecule (class of molecules), explaining why it is so widely distributed among prokaryotes and eukaryotes. In fact, melanin is believed to have been spawned many times over through convergent evolution.

An Exceedingly Exceptional Code

I’m not sure how I missed this one. Recall that only one of a million randomly generated codes was more error-proof that the genetic code used by life. Well, in turns out the frequency of amino acids used by all three domains of life is much the same. And when you factor for this frequency of amino acid use, the genetic code is actually much better than “one in a million”:

We found that taking the amino-acid frequency into account decreases the fraction of random codes that beat the natural code. This effect is particularly pronounced when more refined measures of the amino-acid substitution cost are used than hydrophobicity. To show this, we devised a new cost function by evaluating in silico the change in folding free energy caused by all possible point mutations in a set of protein structures. With this function, which measures protein stability while being unrelated to the code’s structure, we estimated that around two random codes in a billion (10^9) are fitter than the natural code. When alternative codes are restricted to those that interchange biosynthetically related amino acids, the genetic code appears even more optimal.

[Gilis D, Massar S, Cerf NJ, Rooman M. 2001. Optimality of the genetic code with respect to protein stability and amino-acid frequencies. Genome Biol. 2(11):RESEARCH0049]

The Increasing Hydrophobicity Effect

I have argued that the genetic code may have been designed to exploit the mutagenic bias that exists as a consequence of cytosine deamination. In my original analysis, I noted that the genetic code uses cytosine deamination to channel mutations such that they sample from an pool of amino acids that is almost exclusively hydrophobic (IHE or Increasing Hydrophobicity Effect). Furthermore, this pool is biased toward facilitating secondary structure formation. If coupled with carefully chosen initial proteomes, the potential exists that the first major evolutionary steps subsequent to the originally designed state where rigged such that the mutational bias could untap secondary designs that were front-loaded into the original state. For example, this might mean that something like the evolution of multicellularity (and perhaps more) was designed through this biased mutagenic effect.

The first step in testing this hypothesis is to determine whether the IHE plays out in evolution. Since the genetic code is universal, we might expect to see residual traces of this effect even if the sole intention of the design was to guide the first major evolutionary steps. Two extensive analyses have indeed uncovered the IHE in action (although neither paper makes the connection I did in my original analysis).

Bacteria Plan Ahead, Anticipating Future Events

Just as humans have learned to connect dark clouds with rain, so too have bacteria and yeast learned to use one event to predict the arrival of another.

Read the rest.

Front-loading with ribosomes

While outlining the logic of front-loading in The Design Matrix, I noted how the existence of multifunctional (moonlighting) proteins would serve the needs of front-loading. In essence, a protein with multiple functions can be viewed as a protein that is packed with preadaptations ready to be more fully exploited when the proper conditions arise.

This developing paradigm has allowed me to come up with a prediction. If evolution was front-loaded, and a significant aspect of this front-loading existed as multifunctional proteins, whereby secondary or tertiary functions could be unleashed as evolution proceeded into the future, an excellent candidate for storage of some of these secondary functions would be the ribosome, the protein-synthesizing factory of the cell. This is because a designer could count on the ribosome being retained, largely unchanged, throughout billions of years of evolution because it plays such an absolutely essential role in life. If it remains largely unchanged, secondary functions can be carried into the future. Thus, I would predict that ribosomal proteins, which normally function as chaperones to fold the ribosomal RNA and hold it together to form the functioning ribosome, would also exhibit secondary functions (moonlight).

And a survey of the literature does indeed support this prediction.

Here’s to You, Mr. DM Reader

Taking a break

Cells Are Like Robust Computational Systems

Gene regulatory networks in cell nuclei are similar to cloud computing networks, such as Google or Yahoo!, researchers report today in the online journal Molecular Systems Biology. The similarity is that each system keeps working despite the failure of individual components, whether they are master genes or computer processors.

[…]

“It’s extremely rare in nature that a cell would lose both a master gene and its backup, so for the most part cells are very robust machines,” said Anthony Gitter, a graduate student in Carnegie Mellon’s Computer Science Department and lead author of the Nature MSB article. “We now have reason to think of cells as robust computational devices, employing redundancy in the same way that enables large computing systems, such as Amazon, to keep operating despite the fact that servers routinely fail.”

-HERE

Genomes and LUCA

Continuing our hunt for LUCA, we have “A minimal estimate for the gene content of the last universal common ancestor—exobiology from a terrestrial perspective” by Christos Ouzounis , Victor Kunin, Nikos Darzentas, and Leon Goldovsky (Research in Microbiology 157 (2006) 57–68).   This research compared 184 completed genomes from the three domains in the search for LUCA.

Cat Plays Tennis